The evaluation of zebrafish cardiovascular and behavioral functions through microfluidics

This study proposed a new experimental approach for the vascular and phenotype evaluation of the non-anesthetized zebrafish with representative imaging orientations for heart, pectoral fin beating, and vasculature views by means of the designed microfluidic device through inducing the optomotor response and hydrodynamic pressure control. In order to provide the visual cues for better positioning of zebrafish, computer-animated moving grids were generated by an in-house control interface which was powered by the larval optomotor response, in conjunction with the pressure suction control. The presented platform provided a comprehensive evaluation of internal circulation and the linked external behaviors of zebrafish in response to the cardiovascular parameter changes. The insights from these imaging sections was extended to identify the linkage between the cardiac parameters and behavioral endpoints. In addition, selected chemicals such as ethanol and caffeine were employed for the treatment of zebrafish. The obtained findings can be applicable for future investigation in behavioral drug screening serving as the forefront in psychopharmacological and cognition research.

Blue as an Underrated Alternative to Green: Photoplethysmographic Heartbeat Intervals Estimation under Two Temperature Conditions

Since photoplethysmography (PPG) sensors are usually placed on open skin areas, temperature interference can be an issue. Currently, green light is the most widely used in the reflectance PPG for its relatively low artifact susceptibility. However, it has been known that hemoglobin absorption peaks at the blue part of the spectrum. Despite this fact, blue light has received little attention in the PPG field. Blue wavelengths are commonly used in phototherapy. Combining blue light-based treatments with simultaneous blue PPG acquisition could be potentially used in patients monitoring and studying the biological effects of light. Previous studies examining the PPG in blue light compared to other wavelengths employed photodetectors with inherently lower sensitivity to blue, thereby biasing the results. The present study assessed the accuracy of heartbeat intervals (HBIs) estimation from blue and green PPG signals, acquired under baseline and cold temperature conditions. Our PPG system is based on TCS3472 Color Sensor with equal sensitivity to both parts of the light spectrum to ensure unbiased comparison. The accuracy of the HBIs estimates, calculated with five characteristic points (PPG systolic peak, maximum of the first PPG derivative, maximum of the second PPG derivative, minimum of the second PPG derivative, and intersecting tangents) on both PPG signal types, was evaluated based on the electrocardiographic values. The statistical analyses demonstrated that in all cases, the HBIs estimation accuracy of blue PPG was nearly equivalent to the G PPG irrespective of the characteristic point and measurement condition. Therefore, blue PPG can be used for cardiovascular parameter acquisition. This paper is an extension of work originally presented at the 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Monoaminergic Receptors as Modulators of the Perivascular Sympathetic and Sensory CGRPergic Outflows

Blood pressure is a highly controlled cardiovascular parameter that normally guarantees an adequate blood supply to all body tissues. This parameter is mainly regulated by peripheral vascular resistance and is maintained by local mediators (i.e., autacoids), and by the nervous and endocrine systems. Regarding the nervous system, blood pressure can be modulated at the central level by regulating the autonomic output. However, at peripheral level, there exists a modulation by activation of prejunctional monoaminergic receptors in autonomic- or sensory-perivascular fibers. These modulatory mechanisms on resistance blood vessels exert an effect on the release of neuroactive substances from the autonomic or sensory fibers that modify blood pressure. Certainly, resistance blood vessels are innervated by perivascular: (i) autonomic sympathetic fibers (producing vasoconstriction mainly by noradrenaline release); and (ii) peptidergic sensory fibers [producing vasodilatation mainly by calcitonin gene-related peptide (CGRP) release]. In the last years, by using pithed rats, several monoaminergic mechanisms for controlling both the sympathetic and sensory perivascular outflows have been elucidated. Additionally, several studies have shown the functions of many monoaminergic auto-receptors and hetero-receptors expressed on perivascular fibers that modulate neurotransmitter release. On this basis, the present review: (i) summarizes the modulation of the peripheral vascular tone by adrenergic, serotoninergic, dopaminergic, and histaminergic receptors on perivascular autonomic (sympathetic) and sensory fibers, and (ii) highlights that these monoaminergic receptors are potential therapeutic targets for the development of novel medications to treat cardiovascular diseases (with some of them explored in clinical trials or already in clinical use).

Analysis for the Influence of ABR Sensitivity on PTT-Based Cuff-Less Blood Pressure Estimation before and after Exercise

An accurate and continuous measurement of blood pressure (BP) is of great importance for the prognosis of some cardiovascular diseases in out-of-hospital settings. Pulse transit time (PTT) is a well-known cardiovascular parameter which is highly correlated with BP and has been widely applied in the estimation of continuous BP. However, due to the complexity of cardiovascular system, the accuracy of PTT-based BP estimation is still unsatisfactory. Recent studies indicate that, for the subjects before and after exercise, PTT can track the high-frequency BP oscillation (HF-BP) well, but is inadequate to follow the low-frequency BP variance (LF-BP). Unfortunately, the cause for this failure of PTT in LF-BP estimation is still unclear. Based on these previous researches, we investigated the cause behind this failure of PTT in LF-BP estimation. The heart rate- (HR-) related arterial baroreflex (ABR) model was introduced to analyze the failure of PTT in LF-BP estimation. Data from 42 healthy volunteers before and after exercise were collected to evaluate the correlation between the ABR sensitivity and the estimation error of PTT-based BP in LF and HF components. In the correlation plot, an obvious difference was observed between the LF and HF groups. The correlation coefficient r for the ABR sensitivity with the estimation error of systolic BP (SBP) and diastolic BP (DBP) in LF was 0.817 ± 0.038 and 0.757 ± 0.069, respectively. However, those correlation coefficient r for the ABR sensitivity with the estimation error of SBP and DBP in HF was only 0.403 ± 0.145 and 0.274 ± 0.154, respectively. These results indicated that there is an ABR-related complex LF autonomic regulation mechanism on BP, PTT, and HR, which influences the effect of PTT in LF-BP estimation.

Corrigendum

Fuhrman J. Dietary Protocols to Maximize Disease Reversal and Long-Term Safety. American Journal of Lifestyle Medicine. 2015; 9: 343-353. Original DOI: 10.1177/1559827615580971 Fuhrman J, Michael S. Improved Cardiovascular Parameter with a Nutrient-Dense, Plant-Rich Diet-Style: A Patient Survey with Illustrative Cases. American Journal of Lifestyle Medicine. 2017; 11: 264-273. Original DOI: 10.1177/1559827615611024 In the above articles, the author disclosed the following financial relationships: The author maintains a website at https://www.drfuhrman.com , which sells nutritional supplements and other health-related products. The author also serves on the Executive Board of the Nutritional Research Foundation, a non-profit that promotes clinical research that includes nutritional interventions on chronic diseases, and includes the Fuhrman Longevity Society among its initiatives. More information is available at its website at https://www.nutritionalresearch.org .

Cardiovascular Modeling With Adapted Parametric Inference

Computational modeling of the cardiovascular system, promoted by the advance of fluid-structure interaction numerical methods, has made great progress towards the development of patient-specific numerical aids to diagnosis, risk prediction, intervention and clinical treatment. Nevertheless, the reliability of these models is inevitably impacted by rough modeling assumptions. A strong in-tegration of patient-specific data into numerical modeling is therefore needed in order to improve the accuracy of the predictions through the calibration of important physiological parameters. The Bayesian statistical framework to inverse problems is a powerful approach that relies on posterior sampling techniques, such as Markov chain Monte Carlo algorithms. The generation of samples re-quires many evaluations of the cardiovascular parameter-to-observable model. In practice, the use of a full cardiovascular numerical model is prohibitively expensive and a computational strategy based on approximations of the system response, or surrogate models, is needed to perform the data as-similation. As the support of the parameters distribution typically concentrates on a small fraction of the initial prior distribution, a worthy improvement consists in gradually adapting the surrogate model to minimize the approximation error for parameter values corresponding to high posterior den-sity. We introduce a novel numerical pathway to construct a series of polynomial surrogate models, by regression, using samples drawn from a sequence of distributions likely to converge to the posterior distribution. The approach yields substantial gains in efficiency and accuracy over direct prior-based surrogate models, as demonstrated via application to pulse wave velocities identification in a human lower limb arterial network.